Business Intelligence (BI) Critical Success Factors

Companies are increasingly focussing their information systems efforts around Business Intelligence (BI) solutions. The benefits realised from BI vary significantly from company to company. BI systems are now being used as extensions of Enterprise Resource Planning (ERP) systems as they consolidate, transform and analyse the vast amounts of data generated by the firm. Much attention has been given to the identification of critical success factors (CSF) associated with the adoption of ERP systems. However, there is only limited research that has focussed on the CSF associated with BI implementations as part of an ERP system environment. Hence, this research documents BI specific critical success factors that industry partners, venders or systems users have identified in their presentations at conferences, education forms or formal user group meetings

Examining Quality Factors Influencing the Success of Data Warehouse

Increased organizational dependence on data warehouse (DW) systems has drived the management attention towards improving data warehouse systems to a success. However, the successful implementation rate of the data warehouse systems is low and many firms do not achieve intended goals. A recent study shows that improves and evaluates data warehouse success is one of the top concerns facing IT/DW executives. Nevertheless, there is a lack of research that addresses the issue of the data warehouse systems success. In addition, it is important for organizations to learn about quality needs to be emphasized before the actual data warehouse is built. It is also important to determine what aspects of data warehouse systems success are critical to organizations to help IT/DW executives to devise effective data warehouse success improvement strategies. Therefore, the purpose of this study is to further the understanding of the factors which are critical to evaluate the success of data warehouse systems. The study attempted to develop a comprehensive model for the success of data warehouse systems by adapting the updated DeLone and McLean IS Success Model. Researcher models the relationship between the quality factors on the one side and the net benefits of data warehouse on the other side. This study used quantitative method to test the research hypotheses by survey data. The data were collected by using a web-based survey. The sample consisted of 244 members of The Data Warehouse Institution (TDWI) working in variety industries around the world. The questionnaire measured six independent variables and one dependent variable. The independent variables were meant to measure system quality, information quality, service quality, relationship quality, user quality, and business quality. The dependent variable was meant to measure the net benefits of data warehouse systems. Analysis using descriptive analysis, factor analysis, correlation analysis and regression analysis resulted in the support of all hypotheses. The research results indicated that there are statistically positive causal relationship between each quality factors and the net benefits of the data warehouse systems. These results imply that the net benefits of the data warehouse systems increases when the overall qualities were increased. Yet, little thought seems to have been given to what the data warehouse success is, what is necessary to achieve the success of data warehouse, and what benefits can be realistically expected. Therefore, it appears nearly certain and plausible that the way data warehouse systems success is implemented in the future could be changed

Data Warehousse : marco de calidad

“La memoria propone una serie de guías de actuación para abordar con garantías de éxito el desarrollo de sistemas que incluyan un almacén de datos central o Data warehouse”. Con la memoria nos centramos en el desarrollo teórico del ámbito que rodea al Data Warehouse y sus relaciones con el resto de componentes que forman parte de un sistema de Business Intelligence. Para poder conseguir las guías de actuación nos basamos en los estándares, normas de calidad o guías de buenas prácticas punteros de la actualidad. El principal punto productivo de la memoria es que se propone un marco de calidad adaptado a las necesidades que un Data Warehouse necesita disponer para que pueda ser desarrollado con las mayores garantías de éxito posibles. Se ha dividido la estructura del documento en cuatro bloques. 1. Con el primer bloque del texto hacemos un resumen del conocimiento que existe sobre soluciones de Business Intelligence centrándonos en primera instancia en qué son para llegar al detalle de su componente más crítico, el Data Warehouse. Se hace especial énfasis en conocer qué es un Data Warehouse, cómo se crea y mantiene y cómo puede explotarse para saber cómo adaptar los puntos fuertes de otros marcos de calidad para nuestros objetivos. Por ello, seguidamente pasamos a explicar el contexto que rodea a los Data Warehouse para saber la forma en la que se desarrollan y encajan sus componentes. Veremos un repaso histórico de cómo han ido evolucionando las soluciones que incorporan Data Warehouse para conocer a partir de ahí las metodologías más importantes que se han desarrollado. Las metodologías más importantes giran en torno a las filosofías de Kimball e Inmon cuyos enfoques son totalmente opuestos, ya que la de Kimball (o Bottom-Up) se centra en el detalle y construye la solución desde lo específico a lo genérico y la de Inmon (Top-Down) parte de construir la solución desde lo genérico para a partir de ahí propagar la solución detallada. 2. Dado que nos centramos en crear un marco de calidad, con el segundo bloque de la memoria hacemos un repaso de los estándares, normas de calidad y guías de buenas prácticas que podremos aplicar a través de un estudio sobre el estado del arte actual e identificando los puntos más adecuados para nuestras guidelines. No solo nos centraremos en la calidad de los datos sino que también haremos un estudio de la calidad de los procesos, desde la implementación del propio DW hasta su explotación, gestión del proyecto de desarrollo etc. Por ello el segundo bloque tiene dos divisiones claras y diferenciadas, la centrada en la gestión y los procesos y la centrada en el dato y sus características. 3. Con el tercer bloque (y objetivo de la memoria) podemos ver el resultado depurado del resto de la memoria ya que obtenemos las directrices que nos sirven de punto de partida para producir DW de calidad que sean fiables para usar en soluciones de BI. 4. No se quería formar un documento puramente teórico, por lo que en la cuarta parte de la memoria nos centramos en el uso de dos herramientas de la familia Microsoft que nos permiten acercar las guidelines al proceso crucial de creación de un DW, el proceso de Extracción, Transformación y Carga de datos (ETL) de los sistemas origen en la base de datos destino que forma el propio DW.Las herramientas son Biztalk Server 2010 para solucionar problemas de interoperabilidad y asegurar que la tarea de Extracción se realice sin problemas y la segunda será SQL Server Integration Services, que propone muchas facilidades para completar el ETL con garantías. ------------------------------------------------------------------------------------------"The document proposes an action guide for dealing with guarantees of success developing systems that include a Data Warehouse."With memory we focus on the theoretical development of the area surrounding the Data Warehouse and its relations with the other components that are part of a business intelligence system. For guidelines, we rely on quality standards and best practice guidelines pointers today. The added value of the document as a framework adapted to the needs of a data warehouse needs to have in order to be developed with greater guarantees of success possible. Structure has been divided into four blocks of the document. 1) The first block of text is a summary of existing knowledge on Business Intelligence solutions. We focus primarily on what are BI solutions to reach the detail of your most critical component, the Data Warehouse. We focus with a special interest in knowing what a Data Warehouse is, how it is created and maintained and how it can be exploited. Paragraph is important to know how to adapt the strengths of other quality frameworks for our purposes. Therefore, we will explain below the context around the data warehouse to know the manner in which they develop and fit components. We will see a historical review of how the solutions have evolved to incorporate Data Warehouse to know from there the most important methodologies that have been developed. The most important methods revolve around the Inmon and Kimball philosophies whose approaches are opposites, as Kimball (or Bottom-Up) focuses on the detail and build the solution from the specific to the generic and the Inmon (Top-Down) part of building the solution from the generic to propagate from there detailed solution. 2) As we focus on building a quality framework, with the second block of memory we review quality standards and best practice guidelines that can be applied through a study on the state of the art and identifying the most suitable to our guidelines. We will focus on both the quality of data and the quality of the process, since the implementation of the DW itself to exploitation, development project management etc. Thus the second block has two clear and distinct divisions, focused on managing the processes and the data-based and property. 3) The third block (and objective memory) shows the result of the rest of the memory and we get the guidelines that serve as a starting point for producing quality DW reliable for use in BI solutions. 4) We want to provide practical content to memory so in the fourth block, we focus on the use of two Microsoft tools that allow us to bring the guidelines to the process of creating a DW, the process of extraction, transformation and loading of data (ETL) from the source system to the target database that is itself DW. Tools are Biztalk Server 2010 to solve interoperability problems and ensure that the task of extraction goes smoothly and the second is SQL Server Integration Services, which offers many facilities to complete the ETL with guarantees.Ingeniería Técnica en Informática de Gestió

Business intelligence for sustainable competitive advantage: the case of telecommunications companies in Malaysia

The concept of Business Intelligence (BI) as an essential competitive tool has been widely emphasized in the strategic management literature. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well explained. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage.Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.This research uses combination of theoretical foundation of resource-based theory and diffusion of innovation theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. Qualitative field study then is carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of business analysts and decision makers in telecommunications firms and is analyzed by Partial Least Square-based Structural Equation Modeling.The findings revealed that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management will have better chance in realizing their dreams of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility and observability are also significant in ensuring BI success. It thus implied that the executives’ positive perceptions towards BI initiatives are deemed necessary. Moreover, the most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social and environmental issues.The BI model well explained how BI was deployed in Malaysian telecommunications companies. This study thus contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts

Business intelligence information systems success : a South African study.

Doctor of Philosophy in Information Systems and Technology. University of KwaZulu-Natal. Durban, 2016.Business Intelligence (BI) systems hold promise for improving organisational decision making in South Africa. Additionally, BI systems have become increasingly important over the past few decades and are one of the top spending priority areas of most organisations. Yet till now, the factors influencing the success of BI systems in South Africa have not been fully investigated. The study found no scholarly research for managers and other practitioners to assess post implementation success of BI systems in South Africa. This lack of research may directly affect managers’ not knowing how best to implement BI systems and could thereby delay the successful implementation of BI systems in South African organisations. The study extends that of DeLone and McLean (2003), conducted in developed economies by applying it to a developing economy context, namely South Africa. The DeLone and McLean (2003) model has been widely utilised to study factors that influence information systems (IS) success. This study extends the DeLone and McLean (2003) by adding a user quality factor and suggests a theoretical model consisting of six factors, which are: (1) system quality, (2) service quality, (3) information quality, (4) user satisfaction, (5) individual impact, (6) and user quality. The theoretical model was formulated from the literature review. It was then validated and enhanced through a qualitative study of three interviews with end users of BI systems based in South Africa. The theoretical model was then presented to a panel of experts for verification. A questionnaire survey method was employed as the main method to collect data and to answer the main research question. Statistical analysis methods and Structural Equation Modelling (SEM) with SPSS was used to analyse the data. The results of the hypotheses were mixed. Three suggested that relationships were statistically significant, while the other four did not. The study finds that information quality is significantly and positively related to user satisfaction in a BI system. The results also indicate that user quality is positively related to user satisfaction in a BI system and system quality is positively related to individual impact in a BI system. The results have both managerial and research implications. The results of this study will add value to IS and specifically BI literature. Organisations, which have adopted BI or are planning to adopt BI, can use the important variables of the study to undertake an internal check to find out how they compare in terms of these variables. The unique contribution of this study is the identification of post implementation success factors of BI systems in a South African context. The factors identified also served in providing a set of management guidelines for the BI environment in South Africa